A semi-theoretical approach to determine shear wave velocity log using MLR method with a hypothetical test on core and well log data

Author(s):  
Javid Hassanzadeh Azar ◽  
Abdolrahim Javaherian ◽  
Mahmoud Reza Pishvaie
2020 ◽  
Vol 173 ◽  
pp. 103932
Author(s):  
Bo Yu ◽  
Hui Zhou ◽  
Handong Huang ◽  
Hanming Chen ◽  
Lingqian Wang ◽  
...  

2014 ◽  
Vol 62 (4) ◽  
pp. 818-848 ◽  
Author(s):  
Raoof Gholami ◽  
Ali Moradzadeh ◽  
Vamegh Rasouli ◽  
Javid Hanachi

2017 ◽  
Vol 2 (2) ◽  
pp. 181-194
Author(s):  
Ziba Hosseini ◽  
Ali Kadkhodaie ◽  
Sajjad Gharechelou ◽  
◽  
◽  
...  

2013 ◽  
Vol 5 (2) ◽  
Author(s):  
Mojtaba Asoodeh ◽  
Parisa Bagheripour

AbstractShear wave velocity is a critical physical property of rock, which provides significant data for geomechanical and geophysical studies. This study proposes a multi-step strategy to construct a model estimating shear wave velocity from conventional well log data. During the first stage, three correlation structures, including power law, exponential, and trigonometric were designed to formulate conventional well log data into shear wave velocity. Then, a Genetic Algorithm-Pattern Search tool was used to find the optimal coefficients of these correlations. Due to the different natures of these correlations, they might overestimate/underestimate in some regions relative to each other. Therefore, a neuro-fuzzy algorithm is employed to combine results of intelligently derived formulas. Neuro-fuzzy technique can compensate the effect of overestimation/underestimation to some extent, through the use of fuzzy rules. One set of data points was used for constructing the model and another set of unseen data points was employed to assess the reliability of the propounded model. Results have shown that the hybrid genetic algorithm-pattern search technique is a robust tool for finding the most appropriate form of correlations, which are meant to estimate shear wave velocity. Furthermore, neuro-fuzzy combination of derived correlations was capable of improving the accuracy of the final prediction significantly.


Solid Earth ◽  
2019 ◽  
Vol 10 (2) ◽  
pp. 379-390 ◽  
Author(s):  
Yaniv Darvasi ◽  
Amotz Agnon

Abstract. Instrumental strong motion data are not common around the Dead Sea region. Therefore, calibrating a new attenuation equation is a considerable challenge. However, the Holy Land has a remarkable historical archive, attesting to numerous regional and local earthquakes. Combining the historical record with new seismic measurements will improve the regional equation. On 11 July 1927, a rupture, in the crust in proximity to the northern Dead Sea, generated a moderate 6.2 ML earthquake. Up to 500 people were killed, and extensive destruction was recorded, even as far as 150 km from the focus. We consider local near-surface properties, in particular, the shear-wave velocity, as an amplification factor. Where the shear-wave velocity is low, the seismic intensity far from the focus would likely be greater than expected from a standard attenuation curve. In this work, we used the multichannel analysis of surface waves (MASW) method to estimate seismic wave velocity at anomalous sites in Israel in order to calibrate a new attenuation equation for the Dead Sea region. Our new attenuation equation contains a term which quantifies only lithological effects, while factors such as building quality, foundation depth, topography, earthquake directivity, type of fault, etc. remain out of our scope. Nonetheless, about 60 % of the measured anomalous sites fit expectations; therefore, this new ground-motion prediction equation (GMPE) is statistically better than the old ones. From our local point of view, this is the first time that integration of the 1927 historical data and modern shear-wave velocity profile measurements improved the attenuation equation (sometimes referred to as the attenuation relation) for the Dead Sea region. In the wider context, regions of low-to-moderate seismicity should use macroseismic earthquake data, together with modern measurements, in order to better estimate the peak ground acceleration or the seismic intensities to be caused by future earthquakes. This integration will conceivably lead to a better mitigation of damage from future earthquakes and should improve maps of seismic hazard.


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